Responsibilitie
About the team The AI Data and Safety team plays a critical role in advancing Seed foundational models across modalities and improving AI-native applications built on the Seed model series. We work across the data lifecycle, from defining evaluation approaches and translating user feedback and benchmark outcomes into data requests, to building scalable processes that improve data quality and support rapid model iteration. Our team combines technical and operational capabilities, bringing together multidisciplinary talent across product management, data engineering, and data operations. Our work is driven by people who think deeply about model behavior, move quickly to solve complex problems, and bring first-hand experience as both builders and users of models and agents. In close partnership with Seed researchers, industry experts, and leading data vendors, we tackle challenging data problems at the frontier of AI development, helping improve both model performance and user experience. Responsibilities - Collaborate with technical teams to precisely define the data requirements necessary for aligning Large Language Models (LLMs) across global markets. - Develop methodologies for data acquisition and production, while also monitoring costs and assessing the effectiveness and efficiency of these processes. Ensure data quality is maintained at high standards and continually enhance processes based on both quantitative and qualitative feedback. - Evaluate the impact of data production tools on the effectiveness and quality of data production. Work closely with technical teams to enhance both the quality and effectiveness of these tools. - Proactively identify and mitigate potential biases and vulnerabilities in the data production process. This includes, but is not limited to, addressing human and system biases through the implementation of technical, product, and operational solutions.
Qualification
Minimum Qualifications - Solid understanding of alignment and related approaches, such as Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), and others. Or solid experience in moderation, labeling, search quality, or data synthesis. - Minimum of two years of experience as a product manager or product strategist, including process design experience. Preferred Qualifications - A strong interest in both LLMs and human behavior/experience/wellbeing. - Collaborative team player who knows how to assertively advocate for their ideas without being overbearing. - Skilled in maintaining attention to detail while staying focused on prioritized goals and the bigger picture.
Job Information
【For Pay Transparency】Compensation Description (Annually)
The base salary range for this position in the selected city is $228000 - $462000 annually.
Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.
Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
The Company reserves the right to modify or change these benefits programs at any time, with or without notice.
For Los Angeles County (unincorporated) Candidates:
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:
1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
3. Exercising sound judgment.
